About the roleYou'll own the experimentation and data platform end to end - from the research UI down to the data infrastructure, the models, and compute underneath it. This platform powers the data and strategy behind our market operations - battery optimization, DART/PTP, CRR/FTR trading - every strategy that goes live starts here. There's no platform team to hand the unglamorous half to, and no one else to point at when a backtest gives the wrong answer.
It's a lean team with a lot of responsibility per person. No politics, no layers of sign-off - just building and shipping, with the people who'll actually use what you build.
What you'll build- Experimentation platform. Run thousands of backtests and simulations in parallel - point-in-time correct, no look-ahead leakage, fully reproducible and traceable back to the run that produced them. One framework across battery, DART, PTP, and CRR/FTR strategies. Fast and cheap at volume: sweeps across parameters, nodes, and historical periods.
- Data platform. Pipelines for market, weather, forecast, and asset data - ingested, versioned, backfilled, monitored, and quick to extend when a new source shows up. An access layer on top so quants and strategies can pull what they need without waiting on you.
- Forecast platform. Generate the forecasts strategies run on - scheduled, versioned, and monitored. A bad forecast fails silently and shows up as a bad trade.
- Strategy development support and management. Shared tooling so quants go from idea to tested hypothesis without reinventing scaffolding each time - plus the path from experimentation to live trading, with every strategy versioned and traceable from research run to live bid, and CI/CD that makes shipping routine and reversible.
What we're looking for- 5+ years building production systems, including something you took from zero to running
- End-to-end ownership. Comfortable owning the experimentation platform from the researcher/quant-facing UI down through the data infrastructure, compute orchestration, and backtesting engines that support it
- Strong product ownership. You're building for a handful of demanding quants and researchers with no PM in between - you should be able to watch someone iterate on a strategy or model, spot what's actually slowing them down (stale data, slow backtest cycles, brittle pipelines), and design something they'll use without being asked twice
- Tight collaboration with quants and traders -gathering requirements directly from the people running experiments, and turning them around fast
- Directness, and appetite for a domain you are less familiar with. Understanding of quantitative trading, backtesting methodology, or energy markets is a plus, not a requirement - but you'll need to ramp up quickly
- Comfort with the full stack of an experimentation platform: data ingestion and storage at scale, reproducible research environments, versioning of strategies/models/data, and clear observability into what's running and why it succeeded or failed
- An appetite for intensity. This job moves fast and doesn't let up - you should genuinely enjoy that pace, not just tolerate it
